Machine learning to bolster linear services

Augmented content services that make use of machine learning are being showcased on the Amagi stand.

The services being demonstrated include content segmentation and ad-break-point suggestions for linear broadcast. In this example, large volumes of content can be analysed frame by frame in order to segment long-form content, allowing ad breaks to be suggested automatically at logical intervals as per a schedule.

Another use case is automated quality control (QC) in which machine learning helps to perform QC checks to detect black frames, colour bars, clocks and slate frames. For OTT operators, Amagi is showing a new option for automated ad detection. This technology is also powered by an intelligent machine learning-based system and can detect ads from any feed without ad markers.

This enables OTT aggregators to monetise channels without any dependency on TV networks, the company said.

An improved version of the Cloudport playout platform is also being exhibited. New features include the ability to automatically generate a presentation schedule by understanding EPG and ad-break patterns, and an MXF playout option, which is said to save time and space by allowing multiple interpretations of the same asset using different metadata.